Updated search for the standard model Higgs boson in events with jets and missing transverse energy using the full CDF data set

0.32 MB·English

by  CDF Collaboration

Updated search for the standard model Higgs boson in events with jets and missing
transverse energy using the full CDF data set
T. Aaltonen,21 S. Amerio,40 D. Amidei,32 A. Anastassovx,15 A. Annovi,17 J. Antos,12 G. Apollinari,15 J.A. Appel,15
T. Arisawa,53 A. Artikov,13 J. Asaadi,48 W. Ashmanskas,15 B. Auerbach,2 A. Aurisano,48 F. Azfar,39 W. Badgett,15
T. Bae,25 A. Barbaro-Galtieri,26 V.E. Barnes,44 B.A. Barnett,23 P. Barriahh,42 P. Bartos,12 M. Bauceff,40
F. Bedeschi,42 S. Behari,15 G. Bellettinigg,42 J. Bellinger,55 D. Benjamin,14 A. Beretvas,15 A. Bhatti,46 K.R. Bland,5
B. Blumenfeld,23 A. Bocci,14 A. Bodek,45 D. Bortoletto,44 J. Boudreau,43 A. Boveia,11 L. Brigliadoriee,6
C. Bromberg,33 E. Brucken,21 J. Budagov,13 H.S. Budd,45 K. Burkett,15 G. Busettoff,40 P. Bussey,19 P. Buttigg,42
A. Buzatu,19 A. Calamba,10 S. Camarda,4 M. Campanelli,28 F. Canellioo,11,15 B. Carls,22 D. Carlsmith,55
R. Carosi,42 S. Carrillom,16 B. Casalk,9 M. Casarsa,49 A. Castroee,6 P. Catastini,20 D. Cauz,49 V. Cavaliere,22
M. Cavalli-Sforza,4 A. Cerrif,26 L. Cerritos,28 Y.C. Chen,1 M. Chertok,7 G. Chiarelli,42 G. Chlachidze,15 K. Cho,25
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D. Chokheli,13 M.A. Cioccihh,42 A. Clark,18 C. Clarke,54 M.E. Convery,15 J. Conway,7 M .Corbo,15 M. Cordelli,17
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0 C.A. Cox,7 D.J. Cox,7 M. Cremonesi,42 D. Cruz,48 J. Cuevasz,9 R. Culbertson,15 N. d’Ascenzow,15 M. Dattaqq,15
2 P. De Barbaro,45 L. Demortier,46 M. Deninno,6 F. Devoto,21 M. d’Erricoff,40 A. Di Cantogg,42 B. Di Ruzzaq,15
n J.R. Dittmann,5 M. D’Onofrio,27 S. Donatigg,42 M. Dorigonn,49 A. Driutti,49 K. Ebina,53 R. Edgar,32 A. Elagin,48
a R. Erbacher,7 S. Errede,22 B. Esham,22 R. Eusebi,48 S. Farrington,39 J.P. Ferna´ndez Ramos,29 R. Field,16
J G. Flanaganu,15 R. Forrest,7 M. Franklin,20 J.C. Freeman,15 H. Frisch,11 Y. Funakoshi,53 A.F. Garfinkel,44

8 P. Garosihh,42 H. Gerberich,22 E. Gerchtein,15 S. Giagu,47 V. Giakoumopoulou,3 K. Gibson,43 C.M. Ginsburg,15
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] G. Gomez,9 G. Gomez-Ceballos,30 M. Goncharov,30 O. Gonz´alez Lo´pez,29 I. Gorelov,35 A.T. Goshaw,14
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v D.H. Kim,25 H.S. Kim,25 J.E. Kim,25 M.J. Kim,17 S.B. Kim,25 S.H. Kim,50 Y.K. Kim,11 Y.J. Kim,25 N. Kimura,53
0 M. Kirby,15 K. Knoepfel,15 K. Kondo∗,53 D.J. Kong,25 J. Konigsberg,16 A.V. Kotwal,14 M. Kreps,24 J. Kroll,41
4 M. Kruse,14 T. Kuhr,24 M. Kurata,50 A.T. Laasanen,44 S. Lammel,15 M. Lancaster,28 K. Lannony,36 G. Latinohh,42
4 H.S. Lee,25 J.S. Lee,25 S. Leo,42 S. Leone,42 J.D. Lewis,15 A. Limosanit,14 E. Lipeles,41 H. Liu,52 Q. Liu,44
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. T. Liu,15 S. Lockwitz,56 A. Loginov,56 D. Lucchesiff,40 J. Lueck,24 P. Lujan,26 P. Lukens,15 G. Lungu,46
1 J. Lys,26 R. Lysake,12 R. Madrak,15 P. Maestrohh,42 S. Malik,46 G. Mancaa,27 A. Manousakis-Katsikakis,3
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3 F. Margaroli,47 P. Marinoii,42 M. Mart´ınez,4 K. Matera,22 M.E. Mattson,54 A. Mazzacane,15 P. Mazzanti,6
1 R. McNultyj,27 A. Mehta,27 P. Mehtala,21 C. Mesropian,46 T. Miao,15 D. Mietlicki,32 A. Mitra,1 H. Miyake,50
: S. Moed,15 N. Moggi,6 C.S. Moonaa,15 R. Moorepp,15 M.J. Morelloii,42 A. Mukherjee,15 Th. Muller,24 P. Murat,15
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ar T. Okusawa,38 R. Orava,21 L.Ortolan,4 C. Pagliarone,49 E.Palenciaf,9 P.Palni,35 V. Papadimitriou,15 W. Parker,55
G. Paulettakk,49 M. Paulini,10 C. Paus,30 T.J. Phillips,14 G. Piacentino,42 E. Pianori,41 J. Pilot,36 K. Pitts,22
C. Plager,8 L. Pondrom,55 S. Poprockig,15 K. Potamianos,26 F. Prokoshincc,13 A. Pranko,26 F. Ptohosh,17
G. Punzigg,42 N. Ranjan,44 I. Redondo Ferna´ndez,29 P. Renton,39 M. Rescigno,47 T. Riddick,28 F. Rimondi∗,6
L. Ristori42,15 A. Robson,19 T. Rodriguez,41 S. Rollii,51 M. Ronzanigg,42 R. Roser,15 J.L. Rosner,11 F. Ruffinihh,42
A. Ruiz,9 J. Russ,10 V. Rusu,15 A. Safonov,48 W.K. Sakumoto,45 Y. Sakurai,53 L. Santikk,49 K. Sato,50
V. Savelievw,15 A. Savoy-Navarroaa,15 P. Schlabach,15 E.E. Schmidt,15 T. Schwarz,32 L. Scodellaro,9 F. Scuri,42
S. Seidel,35 Y. Seiya,38 A. Semenov,13 F. Sforzagg,42 S.Z. Shalhout,7 T. Shears,27 P.F. Shepard,43 M. Shimojimav,50
M. Shochet,11 I. Shreyber-Tecker,34 A. Simonenko,13 P. Sinervo,31 K. Sliwa,51 J.R. Smith,7 F.D. Snider,15 V. Sorin,4
H. Song,43 M. Stancari,15 R. St. Denis,19 B. Stelzer,31 O. Stelzer-Chilton,31 D. Stentzx,15 J. Strologas,35 Y. Sudo,50
A. Sukhanov,15 I. Suslov,13 K. Takemasa,50 Y. Takeuchi,50 J. Tang,11 M. Tecchio,32 P.K. Teng,1 J. Thomg,15
E. Thomson,41 V. Thukral,48 D. Toback,48 S. Tokar,12 K. Tollefson,33 T. Tomura,50 D. Tonellif,15 S. Torre,17
D. Torretta,15 P. Totaro,40 M. Trovatoii,42 F. Ukegawa,50 S. Uozumi,25 F. Va´zquezm,16 G. Velev,15 C. Vellidis,15
C. Vernieriii,42 M. Vidal,44 R. Vilar,9 J. Viza´nll,9 M. Vogel,35 G. Volpi,17 P. Wagner,41 R. Wallny,8 S.M. Wang,1
A. Warburton,31 D. Waters,28 W.C. Wester III,15 D. Whitesonb,41 A.B. Wicklund,2 S. Wilbur,11 H.H. Williams,41
2
J.S. Wilson,32 P. Wilson,15 B.L. Winer,36 P. Wittichg,15 S. Wolbers,15 H. Wolfe,36 T. Wright,32 X. Wu,18 Z. Wu,5
K. Yamamoto,38 D. Yamato,38 T. Yang,15 U.K. Yangr,11 Y.C. Yang,25 W.-M. Yao,26 G.P. Yeh,15 K. Yin,15
J. Yoh,15 K. Yorita,53 T. Yoshidal,38 G.B. Yu,14 I. Yu,25 A.M. Zanetti,49 Y. Zeng,14 C. Zhou,14 and S. Zucchelliee6
(CDF Collaboration†)
1Institute of Physics, Academia Sinica, Taipei, Taiwan 11529, Republic of China
2Argonne National Laboratory, Argonne, Illinois 60439, USA
3University of Athens, 157 71 Athens, Greece
4Institut de Fisica d’Altes Energies, ICREA, Universitat Autonoma de Barcelona, E-08193, Bellaterra (Barcelona), Spain
5Baylor University, Waco, Texas 76798, USA
6Istituto Nazionale di Fisica Nucleare Bologna, eeUniversity of Bologna, I-40127 Bologna, Italy
7University of California, Davis, Davis, California 95616, USA
8University of California, Los Angeles, Los Angeles, California 90024, USA
9Instituto de Fisica de Cantabria, CSIC-University of Cantabria, 39005 Santander, Spain
10Carnegie Mellon University, Pittsburgh, Pennsylvania 15213, USA
11Enrico Fermi Institute, University of Chicago, Chicago, Illinois 60637, USA
12Comenius University, 842 48 Bratislava, Slovakia; Institute of Experimental Physics, 040 01 Kosice, Slovakia
13Joint Institute for Nuclear Research, RU-141980 Dubna, Russia
14Duke University, Durham, North Carolina 27708, USA
15Fermi National Accelerator Laboratory, Batavia, Illinois 60510, USA
16University of Florida, Gainesville, Florida 32611, USA
17Laboratori Nazionali di Frascati, Istituto Nazionale di Fisica Nucleare, I-00044 Frascati, Italy
18University of Geneva, CH-1211 Geneva 4, Switzerland
19Glasgow University, Glasgow G12 8QQ, United Kingdom
20Harvard University, Cambridge, Massachusetts 02138, USA
21Division of High Energy Physics, Department of Physics,
University of Helsinki and Helsinki Institute of Physics, FIN-00014, Helsinki, Finland
22University of Illinois, Urbana, Illinois 61801, USA
23The Johns Hopkins University, Baltimore, Maryland 21218, USA
24Institut fu¨r Experimentelle Kernphysik, Karlsruhe Institute of Technology, D-76131 Karlsruhe, Germany
25Center for High Energy Physics: Kyungpook National University,
Daegu 702-701, Korea; Seoul National University, Seoul 151-742,
Korea; Sungkyunkwan University, Suwon 440-746,
Korea; Korea Institute of Science and Technology Information,
Daejeon 305-806, Korea; Chonnam National University,
Gwangju 500-757, Korea; Chonbuk National University, Jeonju 561-756,
Korea; Ewha Womans University, Seoul, 120-750, Korea
26Ernest Orlando Lawrence Berkeley National Laboratory, Berkeley, California 94720, USA
27University of Liverpool, Liverpool L69 7ZE, United Kingdom
28University College London, London WC1E 6BT, United Kingdom
29Centro de Investigaciones Energeticas Medioambientales y Tecnologicas, E-28040 Madrid, Spain
30Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, USA
31Institute of Particle Physics: McGill University, Montr´eal, Qu´ebec H3A 2T8,
Canada; Simon Fraser University, Burnaby, British Columbia V5A 1S6,
Canada; University of Toronto, Toronto, Ontario M5S 1A7,
Canada; and TRIUMF, Vancouver, British Columbia V6T 2A3, Canada
32University of Michigan, Ann Arbor, Michigan 48109, USA
33Michigan State University, East Lansing, Michigan 48824, USA
34Institution for Theoretical and Experimental Physics, ITEP, Moscow 117259, Russia
35University of New Mexico, Albuquerque, New Mexico 87131, USA
36The Ohio State University, Columbus, Ohio 43210, USA
37Okayama University, Okayama 700-8530, Japan
38Osaka City University, Osaka 588, Japan
39University of Oxford, Oxford OX1 3RH, United Kingdom
40Istituto Nazionale di Fisica Nucleare, Sezione di Padova-Trento, ffUniversity of Padova, I-35131 Padova, Italy
41University of Pennsylvania, Philadelphia, Pennsylvania 19104, USA
42Istituto Nazionale di Fisica Nucleare Pisa, ggUniversity of Pisa,
hhUniversity of Siena and iiScuola Normale Superiore, I-56127 Pisa,
Italy, mmINFN Pavia and University of Pavia, I-27100 Pavia, Italy
43University of Pittsburgh, Pittsburgh, Pennsylvania 15260, USA
44Purdue University, West Lafayette, Indiana 47907, USA
45University of Rochester, Rochester, New York 14627, USA
46The Rockefeller University, New York, New York 10065, USA
3
47Istituto Nazionale di Fisica Nucleare, Sezione di Roma 1,
jjSapienza Universita` di Roma, I-00185 Roma, Italy
48Texas A&M University, College Station, Texas 77843, USA
49Istituto Nazionale di Fisica Nucleare Trieste/Udine; nnUniversity of Trieste,
I-34127 Trieste, Italy; kkUniversity of Udine, I-33100 Udine, Italy
50University of Tsukuba, Tsukuba, Ibaraki 305, Japan
51Tufts University, Medford, Massachusetts 02155, USA
52University of Virginia, Charlottesville, Virginia 22906, USA
53Waseda University, Tokyo 169, Japan
54Wayne State University, Detroit, Michigan 48201, USA
55University of Wisconsin, Madison, Wisconsin 53706, USA
56Yale University, New Haven, Connecticut 06520, USA
(Dated: January 21, 2013)
We present an updated search for the Higgs boson produced in association with a vector boson
in the final state with missing transverse energy and two jets. We use the full CDF data set
correspondingtoanintegratedluminosityof9.45fb−1 ataproton-antiprotoncenter-of-massenergy
of√s=1.96TeV.Newtothisanalysisistheinclusionofab-jetidentificationalgorithmspecifically
optimized for H b¯b searches. Across the Higgs boson mass range 90 mH 150 GeV/c2, the
expected 95% cre→dibility level upper limits on the VH production cross≤section≤times the H b¯b
→
branchingfraction areimproved byan averageof 14% relative tothepreviousanalysis. AtaHiggs
boson mass of 125 GeV/c2, the observed (expected) limit is 3.06 (3.33) times the standard model
prediction, corresponding to one of themost sensitive searches todate in this finalstate.
PACSnumbers: 13.85.Rm,14.80.Bn
I. INTRODUCTION
Inthe standardmodelofparticlephysics(SM)[1],the
∗Deceased mechanism of electroweak symmetry breaking generates
†WithvisitorsfromaIstitutoNazionalediFisicaNucleare,Sezione
a massive scalar boson called the Higgs boson (H) [2].
diCagliari,09042Monserrato(Cagliari),Italy,bUniversityofCal-
ifornia Irvine, Irvine, CA 92697, USA, cUniversity of California Overthe lastfew decades there has been anintensive ef-
Santa Barbara, Santa Barbara, CA 93106, USA, dUniversity of fortto uncoverexperimental evidence ofthe existence of
CaliforniaSanta Cruz, Santa Cruz, CA 95064, USA, eInstitute of the Higgsboson. Recently, the CMS andATLAS collab-
Physics,AcademyofSciencesoftheCzechRepublic,18221,Czech orations reported the observation of a new boson with a
Republic,fCERN,CH-1211Geneva,Switzerland,gCornellUniver-
sity, Ithaca, NY 14853, USA, hUniversity of Cyprus, Nicosia CY- mass of approximately 125 GeV/c2 [3]. While the pro-
1678,Cyprus,iOfficeofScience,U.S.DepartmentofEnergy,Wash- duction and decay of this particle are consistent with
ington,DC20585,USA,jUniversityCollegeDublin,Dublin4,Ire- expectationsfortheSMHiggsboson,manyofitsproper-
land,kETH,8092Zu¨rich,Switzerland,lUniversityofFukui,Fukui tieshaveyettobeestablished. Inparticular,therelative
City,Fukui Prefecture, Japan910-0017, mUniversidadIberoamer-
coupling strengths of this boson to quarks, leptons, and
icana, Lomas de Santa Fe, M´exico, C.P. 01219, Distrito Fed-
eral, nUniversity of Iowa, Iowa City, IA 52242, USA, oKinki other bosons are important in understanding whether it
University, Higashi-Osaka City, Japan 577-8502, pKansas State is the SM Higgs boson or another state. While the sen-
University, Manhattan, KS 66506, USA, qBrookhaven National sitivities of the CMS and ATLAS analyses were primar-
Laboratory, Upton, NY 11973, USA, rUniversity of Manchester, ily influenced by decays of this particle into Z bosons,
Manchester M13 9PL, United Kingdom, sQueen Mary, Univer-
W bosons, and photons, the sensitivity of the low-mass
sity of London, London, E1 4NS, United Kingdom, tUniversity
of Melbourne, Victoria 3010, Australia, uMuons, Inc., Batavia, Higgs boson analyses of the CDF and D0 collaborations
IL 60510, USA, vNagasaki Institute of Applied Science, Na- islargelyfromdecaystopairsofbquarks. Recentresults
gasaki 851-0193, Japan, wNational Research Nuclear University, from CDF and D0 show evidence of an excess of events
Moscow 115409, Russia, xNorthwestern University, Evanston, IL consistent with a 125 GeV/c2 SM Higgs boson decaying
60208, USA, yUniversity of Notre Dame, Notre Dame, IN 46556,
to b quarks [4]. However, it is not yet known if this ex-
USA, zUniversidad de Oviedo, E-33007 Oviedo, Spain, aaCNRS-
IN2P3, Paris, F-75205 France, bbTexas Tech University, Lub- cess can be attributed to the same particle observed by
bock, TX 79609, USA, ccUniversidad Tecnica Federico Santa the ATLAS and CMS collaborationsand further investi-
Maria, 110v Valparaiso, Chile, ddYarmouk University, Irbid 211- gation is warranted.
63, Jordan, llUniversite catholique de Louvain, 1348 Louvain-La-
Inthe SM,thedominantdecaychannelforalow-mass
Neuve,Belgium,ooUniversityofZu¨rich,8006Zu¨rich,Switzerland,
ppMassachusetts General Hospital and Harvard Medical School, Higgs boson (mH 135 GeV/c2) is to the b¯b final state.
≤
Boston, MA 02114 USA, qqHampton University, Hampton, VA At the Tevatron, pairs of b quarks are produced via the
23668,USA,rrLosAlamosNationalLaboratory,LosAlamos,NM strong interaction (“QCD multijet” background) with a
87544, USA
cross section much larger than that predicted for Higgs
boson production followed by H b¯b decay. Search-
→
ing for direct Higgs boson production is, therefore, very
4
difficultandfarlesssensitivethansearchingforitinpro- the third-most energetic jet satisfies 15 < Ej3 < 100
T
cesses where the SM Higgs bosonis producedin associa- GeV.Werejecteventswithfourreconstructedjets,where
tionwithaweakvectorbosonV (whereV representsthe each jet exceeds the minimum transverse energy thresh-
W or Z boson). The leptonic decay of the vector boson old (E > 15 GeV) and has pseudorapidity η < 2.4.
T
| |
provides a distinct signature, enabling significant sup- Toreduce contaminationfromQCDmultijet eventsthat
pression of QCD multijet events. Furthermore, selecting exhibitE generatedviajetmismeasurement,theangles
6 T
eventsinwhichjetsareidentifiedasbeingconsistentwith between the E~ and the directions of the second and (if
6 T
the fragmentation of b quarks (“b tagging”) additionally present) third jets are required to be greater than 0.4
improves the signal-to-backgroundratio in low-mass SM radians. To ensure that both leading-E jets are recon-
T
Higgs boson searches. structed within the silicon detector acceptance, they are
OneofthemostsensitiveSMHiggsbosonsearchchan- required to satisfy η < 2, where at least one of them
nels at the Tevatron is the VH → 6ET +b¯b final state, must satisfy |η| < 0|.9|. The QCD multijet background
where6ET representsthe missingtranverseenergyresult- is additionally reduced by 35% using a neural-network
ing fromneutrinos orunidentified chargedleptons inthe regression algorithm that incorporates electromagnetic-
event. This article reports an update to the previous and hadronic-calorimeter quantities to account for jet-
CDFanalysisinthe6ET+b¯bsearchchannel[5]; thesame energy mismeasurements.
data are analyzed, but the b-tagging strategy is signifi-
cantly improved. The complete E +b¯banalysismethod
6 T
hasbeen describedpreviously[5]andwillonlybe briefly
reviewed. Thedatacorrespondtoanintegratedluminos- III. b-JET IDENTIFICATION ALGORITHM
ity of 9.45 fb−1, collected in proton-antiprotoncollisions
at a center-of-mass energy of √s=1.96 TeV.
This analysis employs a multivariate b-tagging al-
gorithm (hobit) specifically optimized for H b¯b
→
searches[16]. Thealgorithmincorporatesquantitiesfrom
II. CDF DETECTOR AND EVENT SELECTION variousCDFb-taggingalgorithmsasinputvariables,and
itassignsanoutputvaluevtoeachjetbasedontheprob-
The CDF II detector is described in detail else- ability that the jet originates from the fragmentation of
where [6, 7]. It features a cylindrical silicon detector a b quark. Jets initiated by b quarks tend to cluster at
and drift wire tracking system inside a superconduct- values close to 1, whereas those initiated by light-flavor
ing solenoid, surrounded by projective calorimeters and quarks are more likely to populate the region near 1.
−
muon detectors. Calorimeter energy deposits are clus- Two operating regions are used: jets with v 0.98 are
≥
tered into jets using a cone algorithm with an opening considered to be tightly tagged (T), whereas jets with
angle of ∆R p(∆φ)2+(∆η)2 = 0.4 [8]. High-pT 0.72 < v < 0.98 are loosely tagged (L). Analogous to
≡
electron candidates are identified by matching charged- the previous analysis, we accept events assigned to one
particle tracks in the inner tracking systems [9, 10] with of three categories based on the tag quality of the two
energy deposits in the electromagnetic calorimeters [11]. leading-ET jets: both jets are tightly tagged (TT); one
Muon candidates are identified by matching tracks with jet is tightly tagged, and the other loosely tagged (TL);
muon-detector track segments [12]. The hermeticity of andonlyonejetistightlytagged(1T).Thetagcategories
the calorimeter in the pseudorapidity range η < 2.4 usedinbothanalysesandtheassociatedtaggingefficien-
| |
providesreliablereconstructionofthemissingtransverse cies of Higgs bosonsignalevents are givenin Table I. As
energy [13, 14]. can be seen, the hobit algorithm achieves a 32% (11%)
Events are selected during online data taking if they relative improvement in the tagging efficiency of signal
contain either E (cal) > 45 GeV, or E (cal) > 35 GeV events into the double-tight (tight-loose) category. The
6 T 6 T
and at least two jets. In the analysis, we further require
that events contain no identified electron or muon, and
E >35GeVaftercorrectionsforinstrumentaleffectsin
6 T TABLE I: Comparison of b-tagging efficiencies per signal
jetreconstructionareapplied[8]. Thetwojetsofgreatest
event in the tag categories of this analysis and the previous
E in the event are required to have transverse energies
thTat satisfy 25 < ETj1 < 200 GeV and 20 < ETj2 < 120 loanbeel[e5d].“JSe”t,satnadggtehdosbeythtahteasreectvatgxgebd-tbayggtihnegjaeltgporriothbmalgaore-
GeV, respectively, according to a jet-energy determina- rithm but not secvtx are labeled “J”. There is no overlap
tion basedon calorimeterdeposits andtrack momentum between the tag categories of a given analysis bydesign.
measurements [15]. This selects candidate events consis-
tent with the ZH νν¯b¯b process. Because τ leptons b-tagging efficiency perevent
Tag category
→
are not explicitly reconstructed and some electrons and Ref. [5] This analysis
muons escape detection or reconstruction, events from Two tight b tags 13.7% (SS) 18.1% (TT)
the WH ℓνb¯b process are also expected to contribute
→ Onetight and one loose b tag 13.1% (SJ) 14.6% (TL)
significantly. Togainsensitivityineventswithanuniden-
Only onetight b tag 31.4% (1S) 31.6% (1T)
tified τ lepton, we therefore also accept events where
5
preselection sample consists of events that satisfy all of
2
the above selection criteria. V/c 104 Data QCD Multijet Top
e V + HF EWK Mistags VV
G
8 (a)
IV. QCD MULTIJET BACKGROUND MODEL s / 103
t
n
e
v 102
In the preselection sample, the dominant background E
to the Higgs boson signal is still that of QCD multijet
production. Other non-neglible backgrounds are those 10
from singly- and pair-produced top quarks (“top”), V-
plus-heavy-flavorjets,dibosonproduction(VV),andjets 1
fromelectroweakprocessesthatareincorrectlytaggedas
0 100 200 300 400
b jets (“electroweak mistags”). The modeling of each Invariant Mass(j,j) (GeV/c2)
background is described in Ref. [5]. A QCD multijet 1 2
background model is derived by looking at data events
0
in a control region where 6ET < 70 GeV and the an- 0.1 104 (b)
gle between the 6E~T and second jet is less than 0.4 ra- s /
dians. The sample of events that satisfy these criteria nt
e
consists almost entirely of QCD multijet contributions. v 103
E
For tag category i (where i = 1T, TL, or TT), a mul-
tivariable probability density function f is formed by
i
taking the ratiobetween taggedand pretaggedevents as 102
a function of several variables. Four of those variables
are the same as in Ref. [5]: the scalar sum of jet trans-
10
verse energies H , the missing track transverse momen-
T
tumoftheevent6pT,andthechargefractions(PipiT/ET,
where the sum is over the tracks within the jet cone) of 0 1 2 3
the first- and second-most energetic jets. To improve ∆φ( E, p)
T T
the modeling of the QCD multijet background, we in-
3
clude two more parameters in the probability density 3
0
function: the number of reconstructed vertices in the 0. 104 (c)
event, which is correlated with the topological variables s /
used in the multivariate discriminants (see Sec. V); and nt
pµ = p sin(µˆ ,ˆj ) + p sin(µˆ ,ˆj ), where p repre- ve 103
⊥ µ1 1 1 µ2 2 2 µi E
sents the momentum of the most energetic muon (if one
exists) within the cone of jet i, and sin(µˆi,ˆji) is the sine 102
oftheanglebetweenthemuonandjetdirections. Thepµ
⊥
variable tends to be large for jets in which the initiating
b quark decays semileptonically through b cℓν. 10
→
A QCD multijet model is determined for each of the
1T, TL, and TT categories by weighting the untagged 0 0.2 0.4 0.6 0.8 1
data in the preselection sample according to the f , Sphericity
1T
f , and f probability density functions, respectively.
TL TT
To determine the appropriate normalization for a given
category, the tagged VV, top, V-plus-heavy-flavor, and FIG. 1: Validation of the background model for all tagged
electroweakmistag backgroundestimates are subtracted eventsinthepreselectionsamplefor(a)theinvariantmassof
from the tagged data, and the multijet prediction is the two leading jets, (b) the angle between the 6E~T and 6~pT,
scaled to that difference. To validate the background and (c) thesphericity of thejets in theevent.
modeling, we compare tagged data and the correspond-
ing combined background prediction in multiple control
regions [17] for various kinematic, angular, and event-
shape variables, which are included later on as inputs to
multivariatediscriminantsthatseparatesignalandback-
ground processes. Shown in Fig. 1 are data-modeling andjet sphericity (eventshape)[18] variables. The good
comparisonsofalltaggedeventsinthe preselectionsam- agreementfound in each distribution is representativeof
plefortheinvariantdijetmass(kinematic),theanglebe- allvariablesincludedintheneural-networkdiscriminants
tween the E~ and ~p directions ∆φ(E~ ,p~ ) (angular), described below.
6 T 6 T 6 T 6 T
6
3 105 41200
s / 0.03 104 VDVH a+t a(H×F10) QEWCDK MMuislttiajegts (aTV)oVp ts / 0.01000 VDVH a+t a(H×F10) QEWCDK MMuislttiajegts TVoVp11002
t n
n e
e v 800 1
v e
E 103 T 0.8 0.85 0.9 0.95 1
1 600
102 (a)
400
10 200
0
0 0.2 0.4 0.6 0.8 1 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1
NN NN (m = 125 GeV/c2)
QCD SIG H
4
0
tFaIgGg.ed2:daTtaheevednisttsriibnutthioenproefsetlhecetiNonNQsaCmDpldeisicnricmominpanatrisfoonr ts / 0. 112400 10
with modeled background expectations. n
e 1
v 100
e
L 0.8 0.85 0.9 0.95 1
T 80
V. MULTIVARIATE DISCRIMINANTS
60 (b)
To optimally separate Higgs boson signal from back-
40
ground, a staged multivariate approach is used. A first
neural network NN is trained to discriminate be- 20
QCD
tween QCD multijet and signal processes. Events that
0
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1
satisfy a minimum NNQCD threshold requirement are NN (m = 125 GeV/c2)
subjectedtoasecondneuralnetworkNN ,designedto SIG H
SIG
separatethe signalfromthe remainingSM backgrounds.
4
The NNQCD discriminant is trained using equal event 0.0 70
yieldsofQCDmultijet-modeledbackgroundandVH sig- s / 60 10
nal processes. As in the previous analysis, the collection nt
e 1
ofinputvariablestotheNNQCD algorithmincludeskine- v 50
e
matic, angular, and event-shape quantities [5, 19], each TT 40 0.8 0.85 0.9 0.95 1
of which is validated with tagged data in the preselec-
tion sample. Figure 2 shows the NNQCD distribution 30 (c)
for tagged events satisfying the preselection criteria. By
20
imposing a minimum NN requirement of 0.6 (which
QCD
defines the signal region), 87% of the signal is retained 10
while 90% of the QCD multijet background is rejected.
Table II shows the expected number of signal and back- 00 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1
groundeventsandthe observeddataeventsinthe signal NNSIG (mH = 125 GeV/c2)
region. For a Higgs boson mass of 125 GeV/c2, we ex-
pect 19 signal events in the 1T category and roughly 11
signal events in both the TL and TT categories. FIG.3: Thedistributionsoftaggeddataeventsandthecorre-
Although the current and previous analyses use the sponding expected backgrounds for the NNSIG discriminant
functions after fitting to data for an assumed Higgs boson
same data set, the selected event samples used are only
massof125GeV/c2. Panel(a)shows1Tevents,(b)showsTL
partiallycorrelateddue toupdatestotheb-taggingalgo-
events,and(c) shows theNNSIG discriminant for TTevents.
rithm and the NN discriminant. Table III shows the
QCD Thesignal contribution (“VH”) assumes aHiggs boson mass
predicted fractions of overlapping signal events between of 125 GeV/c2 and is multiplied by a factor of ten (left un-
the tag categories of the previous analysis and those of scaled in insets) for illustrative purposes. Shown in the inset
this one. As can be seen, only 61% of the TT-tagged is a semilogarithmic version of the same NNSIG distribution
signal events in this analysis were present in the SS tag for eventswith NNSIG >0.8.
category of the previous analysis. The remaining 39%
were classified as SJ events (23%), 1S events (11%), or
were not analyzed (6%) due to either not being tagged
ornotsurvivingtheminimumNN thresholdrequire-
QCD
7
TABLE II: Comparison of the number of expected and observed events in the signal region for different b-tagging categories.
The uncertainties shown include systematic contributions and (when appropriate) statistical uncertainties on the simulation
samples, added in quadraturefor a given process. Thequoted uncertainties for thetotal expected background prediction take
intoaccounttheappropriatecorrelationsamongthesystematicuncertaintiesforeachbackgroundprocess. Signalcontributions
are given for an assumed Higgs boson mass of 125 GeV/c2.
Process 1T TL TT
QCD multijet 5941 178 637 25 222 16
± ± ±
Top 1174 158 302 40 271 34
± ± ±
V + heavy flavorjets 3124 718 286 83 211 65
± ± ±
Electroweak mistags 1070 386 55 21 13 6
± ± ±
Diboson 305 46 48 6 41 5
± ± ±
Total expected background 11612 949 1329 112 759 86
± ± ±
Observeddata 11955 1443 692
ZH νν¯b¯b,ℓℓb¯b 9.7 1.0 5.4 0.5 5.4 0.5
→ ± ± ±
WH ℓνb¯b 9.8 1.0 5.3 0.5 5.3 0.5
→ ± ± ±
VI. RESULTS
TABLE III: Predicted fractions of overlapping signal events
between the previous analysis and this one. The “0T/0S”
categories represent events that do not survive the tagging We perform a binned likelihood fit to search for the
or signal-region definition criteria. Roman-font (italicized) presence of a Higgs boson signal. A combined likelihood
numbers represent percentages of overlapping events relative isformedfromtheproductofPoissonprobabilitiesofthe
to this (the previous) analysis [5]; the sum of the percent-
eventyieldineachbinoftheNN distributionforeach
SIG
ages in each column (row) is 100%. A Higgs boson mass of
tagcategory. Systematicuncertaintiesaretreatedasnui-
125 GeV/c2 is assumed.
sance parameters and incorporated into the limit by as-
0T 1T TL TT sumingGaussianpriorprobabilities,centeredatthenom-
0S — 22% — 19% — 6% inalvalueofthenuisanceparameter,withanRMSwidth
1S 17% — 63% 67% 15% 31% 6% 11% equalto the absolute valueofthe uncertainty. The dom-
inant systematic uncertainties arise from the normaliza-
SJ 12% — 20% 9% 37% 35% 32% 23%
tionoftheV-plus-heavy-flavorbackgroundcontributions
SS 5% — 3% 1% 15% 15% 77% 61%
(30%), differences in b-tagging efficiencies between data
andsimulation(8–16%)[16],uncertaintyonthetop(6.5–
10%) and diboson (6%) cross sections [20, 21], normal-
izations of the QCD multijet background (3–7%), lumi-
nositydetermination(6%)[22],jet-energyscale(6%)[8],
ment. A significant portion of TT signal events is there-
trigger efficiency (1–3%), parton distribution functions
foredifferentfromthesampleofSSeventsintheprevious
(2%), and lepton vetoes (2%). Additional uncertain-
analysis. The percentage of TT data events in this anal-
ties applied only to signal include those on the Higgs
ysis also present in the SS category of the previous one
boson production cross section (5%) [23] and on initial-
is approximately 50%.
and final-state radiation effects (2%). Also included are
The NNSIG discriminant functions trained in the pre- uncertainties in the NNSIG shape, which arise primar-
vious analysis [5] are well modeled in the analogous ho- ily from variations in the jet-energy scale and the QCD
bit categories and also provide good separation of sig- multijet background model.
nal and background events; they were thus retained for ABayesianlikelihoodmethod is usedto set95%cred-
thisanalysis. TheNN discriminantacceptskinematic ibility level (C.L.) upper limits on the SM Higgs bo-
SIG
and angular quantities as input variables, as well as the son production cross section times branching fraction
NN valueandaneural-networkoutputthatattempts σ(VH) (H b¯b). For the signal hypothesis, a flat,
QCD
×B →
to disentangle intrinsic E from instrumental E by us- non-negative prior probability is assumed for the num-
6 T 6 T
ingtrackinginformation[19]. Themodelingofeachinput ber of selected Higgs boson events. The Gaussian priors
variableisvalidatedwithtaggeddatainthesignalregion. of the nuisance parameters are truncated at zero to en-
Figure 3 shows the NN distribution in the signal re- sure non-negative event yield predictions in each NN
SIG SIG
gion(NN >0.6)forthe1T,TL,andTTeventsafter bin. The 95% C.L. limits for the observed data and
QCD
the discriminants from all tag categories were jointly fit- the median-expected outcomes assuming only SM back-
ted to data. grounds are shown in Fig. 4 and Table IV. An average
8
SM Observed SM Observed [5] Obs. (S-J reanalysis)
mit/ Expected mit/ Expected [5] Exp. (S-J reanalysis)
Li ± 1 s.d. expected Li ± 1 s.d. expected
per ± 2 s.d. expected per ± 2 s.d. expected
p p
U U
CL 10 CL 10
% %
5 5
9 9
1
1
90 100 110 120 130 140 150 90 100 110 120 130 140 150
m (GeV/c2) m (GeV/c2)
H H
FIG.4: Observedandexpected(median,forthebackground- FIG.5: Observedandexpected(median,forthebackground-
only hypothesis) 95% C.L. upper limits on VH cross section only hypothesis) 95% C.L. upper limits on Higgs production
times (H b¯b)dividedbytheSMprediction,asafunction inthepreviousanalysis[5]andthoseoftheS-Jreanalysisde-
B →
of the Higgs boson mass. The bands indicate the 68% and scribedinSec.VIIA.Thedarker(black)setoflinesrepresent
95% credibility regions where the limits can fluctuate, in the the observed and expected limits from the previous analysis,
absence of signal. whereas the lighter set (red) represent those of the S-J re-
analysis. The 68% and 95% credibility regions are those of
Ref. [5].
improvementof14%isobtainedinexpectedupperlimits
relative to the previous analysis [5]. The observed limits
lie below the expected values at the level of roughly one 2. Instead of treating the normalization uncertainties
standard deviation for m 120 GeV/c2, and at the of all V-plus-heavy-flavor samples as fully corre-
H
≥
level of approximately two standard deviations for lower lated,the V-plus-heavy-flavorsamplesaregrouped
Higgs boson masses. In constrast, the observed limits of according to flavor content of the final state, with
the previous analysis exceed the median-expected limits eachgroupreceivinga30%uncertainty. Theuncer-
byroughlyonestandarddeviationform >120GeV/c2 tainties associated with each V-plus-heavy-flavor
H
and are in approximate agreement with expected limits grouparetreatedasuncorrelatedwithoneanother.
for lower masses. These differences correspond to a de-
3. An additional E > 35 GeV requirement is made
crease of roughly 55% in the observed limits relative to 6 T
that corresponds to the trigger-level reconstructed
those of the previous analysis [5] independent of m .
H
E value. This has the effect of further reducing
6 T
the QCD multijet background at the few percent
level.
VII. DISCUSSION OF RESULTS
4. As mentioned in Sec. II, upper limits are imposed
We have investigated potential causes for the sizable on jet transverse energies. This is done to avoid
shift in the observed limits. To quantify the impact of a kinematic region susceptible to significant false-
changes to the analysis design and treatment of system- positive tagging rates for the hobit algorithm.
aticuncertainties,wereanalyzethedatasampleusingthe
1S, SJ, and SS categories used in the previous analysis 5. AnadditionalZ-plus-jetssampleisincludedwhere
(Sec.VIIA).Wealsostudytheeffectsfromothersources the Z boson decays to a b¯b pair. The change in
that can influence the observed limits (Sec. VIIB). A overall expected yields due to this additional sam-
summary of the discussion is given in Sec. VIIC. ple is very small as the 6ET here is instrumental.
To estimate the effect of these changes on the limits, we
reanalyze the same data sample using the 1S, SJ, and
A. Reanalysis using 1S, SJ, and SS tagging
categories SS tagging categories of the previous analysis. For this
test, hereafter referred to as the S-J reanalysis, we re-
tain the NN discriminant of the previous analysis so
Besides the change in b-tagging method, there are QCD
that the signal region definitions of this test and that
other less significant changes made in this analysis with
of the previous analysis are the same. The results are
respect to the previous one:
shown in Fig. 5. As can be seen, the expected lim-
1. The b-tag scale factors and their associated uncer- its of Ref. [5] and the S-J reanalysis are in very good
tainties are now handled with an improved treat- agreement. The observedlimits of the S-J reanalysis are
ment of the correlations between tag categories. systematically lower than the observed limits of Ref. [5]
9
TABLE IV: Expected and observed 95% C.L. upper limits on the VH cross section times (H b¯b) divided by the SM
B →
prediction [24].
mH (GeV/c2) 90 95 100 105 110 115 120 125 130 135 140 145 150
Expected 1.57 1.83 1.96 2.08 2.16 2.48 2.80 3.33 4.13 5.26 6.93 9.91 15.55
Observed 0.72 0.94 0.94 0.91 1.32 1.53 1.94 3.06 2.95 3.49 5.35 6.69 11.82
withanaveragedifferenceof 5%form <120GeV/c2 variables(e.g.,jetenergiesandinstantaneousluminosity)
H
and 17% for m 120 Ge−V/c2. For comparison, we hasbeeninvestigated,andanysizabledeviationsrelative
H
− ≥
note that the observed limit for the analysis described to the central predictions are included in the systematic
in this note is 47% lower than that of the S-J reanalysis uncertainties. These scale factors and their associated
at m = 125 GeV/c2. The analysis changes described uncertainties have been propagated through this analy-
H
here thus account for a non-negligible percentage of the sis in a manner consistent with the treatment of b-tag
sizable shift in the observed limits. and mistag scale factors in the other H b¯b CDF anal-
→
We have also investigated the impact of these changes yses [26, 27].
on previously published combined CDF H b¯b lim- To verify that the choice of b-tagging algorithm does
→
its [25]. The NN discriminants of the S-J reanalysis, not result in mismodeling within the high-score regions
SIG
and the updated treatment of systematic uncertainties, of the NN distributions, we validate the background
SIG
arecombinedwiththediscriminantsoftheCDFℓνb¯band model with the data in an electroweak control sample.
ℓℓb¯banalyses[26,27]to obtainanupdated CDFH b¯b For this control sample we require, in addition to the
→
result. Using the discriminants of the S-J reanalysis,the preselection sample criteria, the presence of at least one
localsignificanceoftheCDF-combinedexcessataHiggs identified, isolated electron or muon with a minimum
boson mass of 125 GeV/c2 is recalculated. Within the transverse momentum of 20 GeV/c in the event. The
statistical precision of the calculation, the local signifi- electroweak sample is dominated by backgrounds that
cance is unchanged at 2.7 standard deviations with re- are modeled by simulation and not the QCD multijet
spect to the background-only hypothesis. background,whosemodel is derivedfromdata. Figure 6
showstheNN distributionsforTTandreanalyzedSS
SIG
eventsin the electroweakcontrolregion. As canbe seen,
B. Additional cross-checks there is no obvious difference in the simulation model-
ing ofthe NN discriminantsfor the hobit orsecvtx
SIG
1. Systematic effects from b-tagging algorithms. Comparisons in the 1T-1S and TL-SJ cate-
gories give similar conclusions.
Since switching to a new b-tagging algorithm is the
most significant change adopted for this analysis, it is
important to ensure that the performance of the hobit 2. Effects of statistical fluctuations
algorithm is well understood and well modeled. As with
other b-tagging algorithms, systematic effects associated Theexpectedlimitsaremostsignificantlyimpactedby
with using hobit are taken into account by correcting the bins of the discriminants with the highest signal-to-
the simulation for differences in b-tagging behavior be- background ratios. For the NNSIG distributions, these
tween data and simulation. Two methods are used to are the bins with the highest NNSIG values, as can be
calibrate the simulation, both of which have been used seen in Fig. 3. Because these bins tend to contain only
extensivelyatCDF:onewherethett¯crosssectionisfixed small numbers of data events, the observed limits are
toitstheoreticalprediction,andscalefactorsarederived susceptible to statistical fluctuations. Although we do
that correct the simulation to the b-tag and mistag effi- notknowifthedataeventsarefromsignalorbackground
cienciesmeasuredindata;andanotherwhereheavy-and processes, we explore how a fluctuation of yields from
light-flavor jets are identified with and without electron either type ofprocesswouldmanifestitself inthe NNSIG
conversionswithin them, allowingfor a determinationof distributions. As part of the shift in observed limits is
the same scale factors [16]. As both methods give con- due to the analysischanges mentionedin Sec. VIIA, the
sistent results for the hobit scale factors at both T and yieldsquotedbelowfortheSSandSJresultsreflectthose
L operating points, they are averaged together, result- of the S-J reanalysis and not those of Ref. [5].
ing in b-tag efficiency scale factors of 0.915 0.035 (T) As shown in Table III, we expect significant signal
±
and 0.993 0.035 (L) and mistag efficiency scale fac- event migrations between the tag categories of the pre-
±
tors of 1.50 0.031 (T) and 1.33 0.015 (L), where the vious analysis and those of this one. Consequently, if a
± ±
dominantcontributionstothe uncertaintiesarefromthe Higgs bosonsignalis present, we may observesome very
theoretical uncertainty on the tt¯cross section [28]. The high NN score events in one version of the analysis
SIG
variation of these scale factors with respect to several thateithermigratetoanothertagcategoryordonotap-
10
s / 0.04 102 DV a+t aHF QEWCDK MMuislttiajegts TVoVp TewgAiothBrieLNsENoVSfI:GthPivesarclauenneastlayggsreiessaotaefnrodvthethralenapp0pr.8ien.vgioeuvsenotnsebfeotrwdeeantataegvecnatts-
t (a)
n
e 1T TL TT
v
E 1S 55% 35% 15%
TT 10 SJ 4% 20% 30%
SS 1% 14% 51%
1 effect from background event fluctuations on the differ-
ence between observed limits of the m = 125 GeV/c2
H
0 0.2 0.4 0.6 0.8 1
NN (m = 125 GeV/c2) searches by comparing the number of observed events
SIG H that satisfy NN > 0.8 to the fitted background pre-
SIG
4 102 dictionsforeachtagcategoryinthe currentanalysisand
0.0 (b) theS-Jreanalysis. Forthemostsensitivedouble-tagcat-
s / egories,thepredicted(observed)eventyieldsinthehigh-
t scoreNN regionare37.6 4.6(37)forSSand45.6 5.1
n SIG
ve (62)forSJand39.5 4.6(3±3)forTTand67.4 6.8±(80)
E ± ±
S 10 for TL. While the SJ and TL categories exhibit similar
S upwardfluctuations in data relative to expectations, the
data in the SS (TT) category are consistent with (lower
than) the backgroundexpectation.
A simple test is performed in which 5 data events
1 are added into the high-score region of the TT NNSIG
distribution (maintaining the relative fractions of ob-
0 0.2 0.4 0.6 0.8 1 served events within each high-score bin) to approxi-
NN (m = 125 GeV/c2)
SIG H matelymatchthe expectedbackground,aswasobserved
in the SS category. This change reduces the difference
between the present and S-J reanalyzed limits to 33%.
FIG. 6: Validation of the background model for (a) TT
Combining this effect with that of adding the 3 for-
eventsand(b)reanalyzedSSeventsintheelectroweakcontrol
merly SJ-classified events into the TL category gives a
region.
decrease in observed limits of 19% relative to the S-J
analysis. This is in reasonable agreement with the ex-
pectedimprovement,identifyingthesetwoeffectsindata
pearwithin the otheranalysis. Since the impactofthese
asthe primarysourceofthe changeinobservedlimits at
high-score events on the observed limits can be signifi-
m =125 GeV/c2.
cant, the migration of a few signal-like events between H
tagcategoriesin the S-J reanalysisandthe currentanal- To estimate the probability of an underlying statisti-
ysiscanleadtonon-negligiblechangesinobservedlimits caleffectcausingsuchasizablechangeinobservedlimits,
relative to expectations. Focusing on discriminant out- correlations between the event samples must be under-
puts for the 125 GeV/c2 Higgs boson mass hypothesis, stood. For technical reasons we are not able to deter-
we compare data events in the very highest-score NN mine these correlations separately for each background
SIG
bins of both analyses and find one potential example for process. Instead,welookdirectlyatthedatainthehigh-
this type of event migration. In particular, we observe score regions of the NN discriminants, and calculate
SIG
three events with NN values above 0.9 in the SJ cat- the percentageoverlapbetweenthe tagcategoriesofthis
SIG
egory that are not present in any tag category of the analysis and those of the S-J reanalysis. The overlap
current analysis (the new tagging algorithm categorizes percentages, relative to the current analysis, are given
two of these events as LL and the other as 1L). If these in Table V. Based on these percentages, we use simu-
three data events were to be simply added back into the lated data experiments to estimate the probability that
TL category of the new analysis, the decrease in the ob- the observed limits of this analysis and the S-J reanal-
servedlimits atm =125GeV/c2 with respectto those ysis are compatible. Figure 7 shows a two-dimensional
H
oftheS-Jreanalysiswouldbe reducedfrom47%to31%. distributionofexpectedupperlimits,obtainedfrompro-
The number of expected background events in the ducing pairs of expected outcomes between the hobit
high-score region of the NN discrimimants is also analysis and S-J reanalysis. To calculate a compatibility
SIG
smallandthereforeanadditionalsourceofpotentialsta- probability(p-value),theprobabilityisestimatedforthe
tistical fluctuations in the data that might significantly hobit analysis to be as or more discrepant that what is
impact the observed limits. We check for a potential observed, given the observed limit of the S-J reanalysis.